DESIGN: Exploratory cross-sectional survey administered by trained interviewers among participants of a health screening program.
SETTING: A rural plantation estate in the West Coast of Peninsular Malaysia.
PARTICIPANTS: One hundred and thirty out of 142 adults above 18 years old who attended the program.
MAIN OUTCOME MEASURE: Percentages of respondents reporting realised access and unmet need to health care, determinants of both access indicators and reasons for unmet need. Realised access associated with need but not predisposing or enabling factors and unmet need not associated with any variables were considered equitable.
RESULTS: A total of 88 (67.7%) respondents had visited a doctor (realised access) in the past 6 months and 24.8% (n = 31) experienced unmet need in the past 12 months. Using logistic regression, realised access was associated with presence of chronic disease (OR 6.97, P RM 2000 per month) (OR 51.27, P
DESIGN AND MEASURES: Data were analysed from the Global School-Based Student Health Survey Timor-Leste (n = 3455). An ordered probit model was used to assess the effects of demographic, lifestyle, social, and psychological factors on different levels of worry-related sleep problems (i.e., no, mild and severe sleep problems).
RESULTS: School-going adolescents were more likely to face mild or severe worry-related sleep problems if they were older, passive smokers, alcohol drinkers and moderately active. School-going adolescents who sometimes or always went hungry were more likely to experience worry-related sleep problems than those who did not. Involvement in physical fights, being bullied, and loneliness were positively associated with the probability of having modest or severe worry-related sleep problems.
CONCLUSION: Age, exposure to second-hand smoke, alcohol consumption, physical activity, going hungry, physical fights, being bullied and loneliness are the important determining factors of adolescent worry-related sleep problems. Policymakers should pay special attention to these factors when formulating intervention measures.
MATERIALS AND METHODS: Data from a randomized clinical trial evaluating efficacy of a nonsurgical intervention in women with stress urinary incontinence were used for analyses. The overall score of ICIQ-UI SF ranges from 0 to 21, with greater values indicating increased severity. The ICIQ-LUTSqol ranges from 19 to 76, with greater values indicating increased impact on quality of life. Instruments used in the anchor-based method were the Patient Global Impression of Improvement, patient satisfaction, 1-hour pad test and the incontinence episode frequency. The distribution-based method used an effect size of 0.5 standard deviation. Triangulation of findings was used to converge on a single value of MCID.
RESULTS: At 12-month post-treatment, 106 (88.3%) participants completed the follow-up and were included in the analysis. Anchor-based MCIDs of the ICIQ-UI SF were between 3.4 and 4.4, while the distribution-based MCID was 1.7. Anchor-based MCIDs of the ICIQ-LUTSqol were between 4.8 and 6.9, while the distribution-based MCID was 5.2. Triangulation of findings showed that MCIDs of 4 for ICIQ-UI SF and 6 for ICIQ-LUTSqol were the most appropriate.
CONCLUSION: For women undergoing nonsurgical treatments for incontinence, reductions of 4 and 6 points in ICIQ-UI SF and ICIQ-LUTSqol, respectively are perceived as clinically meaningful.
METHODS: Nationally representative data of Malaysia were used to generate cross-sectional evidence. The sample size was 2156 respondents. An ordered probit regression was utilized to assess factors associated with the practice of physical activity.
RESULTS: Respondents aged 40-49 years with hypertension were 7.3% less likely to participate in high-level physical activity when compared to those without hypertension. The probability of having a low level of physical activity was 12.3% higher among hypertensive patients aged ≥60. Males, married individuals, less-educated adults, low-income earners, and individuals who were aware of their BMI, had a higher tendency to indulge in a highly active lifestyle than others.
CONCLUSION: The effect of hypertension on physical activity was moderated by age. Factors influencing physical activity levels among adults were income, gender, marital status, education, employment status, and BMI awareness.